{
  "id": 11757,
  "url": "https://arxiv.org/abs/2607.16066v1",
  "title": "LLM-Powered Agentic AI for 5G/6G Networks: A Tutorial and Survey on Architectures, Protocols, and Standardization",
  "summary": "Agentic Artificial Intelligence (AI), enabled by Large Language Models, marks a shift from rule-based automation toward autonomous, goal-driven control of Next-Generation Networks (NGNs). Existing surveys treat the two domains in isolation, leaving protocol integration, evaluation, and standardization alignment underexplored. To address this gap, a two-part tutorial-and-survey is presented. Part I formalises the control, management, and AI-native planes of 5G and 6G. It then covers the foundatio",
  "authors": "Mazene Ameur, Abdelkader Mekrache, Bouziane Brik, Adlen Ksentini",
  "category": "research",
  "topics": "safety-alignment,jobs-economy,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-17T15:47:23.000Z",
  "fetched_at": "2026-07-20T05:10:09.534Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/11757",
  "original_url": "https://arxiv.org/abs/2607.16066v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}